PARTICIPATORY MODELLING TO SUPPORT DECISION MAKING IN WATER MANAGEMENT. A CASE STUDY IN THE MIDDLE GUADIANA BASIN, SPAIN.

Resource /Energy Economics and Policy,

An Integrated Assessment approach to linking biophysical modelling and economic valuation tools

Natural resource management (NRM) typically involves complex decisions that affect a variety of stakeholder values. Efficient NRM, which achieves the greatest net environmental, social and financial benefits, needs to integrate the assessment of environmental impacts with the costs and benefits of investment. Integrated assessment (IA) is one approach that incorporates the several dimensions of catchment NRM, by considering multiple issues and knowledge from various disciplines and stakeholders. Despite the need for IA, there are few studies that integrate biophysical modelling tools with economic valuation. In this paper, we demonstrate how economic non-market valuation tools can be used to support an IA of catchment NRM changes. We develop a Bayesian Network model that integrates: a process-based water quality model; ecological assessments of native riparian vegetation; estimates of management costs; and non-market (intangible) values of changes in riparian vegetation. This modelling approach illustrates how information from different sources can be integrated in one framework to evaluate the environmental and economic impacts of NRM actions. It also shows the uncertainties associated with the estimated welfare effects. By estimating the marginal social costs and benefits, a cost-benefit analysis of alternative management intervention can be gained and provides more economic rationality to NRM decisions.Bayesian networks, bio-economic modelling, catchment management, cost-benefit analysis, environmental values, integrated assessment and modelling, non-market valuation, riparian vegetation, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Participatory modelling to support decision making in water management. A case study in the middle Guadiana basin, Spain.

The objective of this research was the implementation of a participatory process for the development of a tool to support decision making in water management. The process carried out aims at attaining an improved understanding of the water system and an encouragement of the exchange of knowledge and views between stakeholders to build a shared vision of the system. In addition, the process intends to identify impacts of possible solutions to given problems, which will help to take decisions

Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods

Commercialization of non-timber forest products (NTFPs) has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed

Integration of biological, economic and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential Baltic salmon management plan

There is a growing need to evaluate fisheries management plans in a comprehensive interdisciplinary context involving stakeholders. In this paper we demonstrate a probabilistic management model to evaluate potential management plans for Baltic salmon fisheries. The analysis is based on several studies carried out by scientists from respective disciplines. The main part consisted of biological and ecological stock assessment with integrated economic analysis of the commercial fisheries. Recreational fisheries were evaluated separately. Finally, a sociological study was conducted aimed at understanding stakeholder perspectives and potential commitment to alternative management plans. In order to synthesize the findings from these disparate studies a Bayesian Belief Network (BBN) methodology is used. The ranking of management options can depend on the stakeholder perspective. The trade-offs can be analysed quantitatively with the BBN model by combining, according to the decision maker’s set of priorities, utility functions that represent stakeholders’ views. We show how BBN can be used to evaluate robustness of management decisions to different priorities and various sources of uncertainty. In particular, the importance of sociological studies in quantifying uncertainty about the commitment of fishermen to management plans is highlighted by modelling the link between commitment and implementation success.Baltic salmon, bio-economic modelling, Bayesian Belief Network, expert knowledge, fisheries management, commitment and implementation uncertainty, management plan, recreational fisheries, stakeholders., Resource /Energy Economics and Policy,

Decision support systems for large dam planning and operation in Africa

Decision support systems/ Dams/ Planning/ Operations/ Social impact/ Environmental effects

Evaluation of Bayesian Networks in Participatory Water Resources Management, Upper Guadiana Basin, Spain

Stakeholder participation is becoming increasingly important in water resources management. In participatory processes, stakeholders contribute by putting forward their own perspective, and they benefit by enhancing their understanding of the factors involved in decision making. A diversity of modeling tools can be used to facilitate participatory processes. Bayesian networks are well suited to this task for a variety of reasons, including their ability to structure discussions and visual appeal. This research focuses on developing and testing a set of evaluation criteria for public participation. The advantages and limitations of these criteria are discussed in the light of a specific participatory modeling initiative. Modeling work was conducted in the Upper Guadiana Basin in central Spain, where uncontrolled groundwater extraction is responsible for wetland degradation and conflicts between farmers, water authorities, and environmentalists. Finding adequate solutions to the problem is urgent because the implementation of the EU Water Framework Directive requires all aquatic ecosystems to be in a “good ecological state” within a relatively short time frame. Stakeholder evaluation highlights the potential of Bayesian networks to support public participation processes